## Tag - Where

### A few thoughts on the existing code parallelization

(This article was first published on Fun with R, and kindly contributed to R-bloggers) A few weeks ago I worked on some old code parallelization. The whole process made me think about how efficient parallelization of the existing code in R can really...

### Data Science Predicting The Future

In this article we will expand on the knowledge learnt from the last article - The What, Where and How of __data Science - and consider how data science is applied to predict the future. By Iliya Valchanov, 365 data Science. comments Predictive analy...

### DataRobot Announces Automated Time Series Solution

DataRobot, the pioneering architects of automated machine learning, announced the general availability of DataRobot Time Series. Following an extensive collaboration with more than 75 customers and world-class data scientists, this latest breakthroug...

### Derivation of Convolutional Neural Network from Fully Connected Network Step-By-Step

What are the advantages of ConvNets over FC networks in image analysis? How is ConvNet derived from FC networks? Where the term convolution in CNNs came from? These questions are to be answered in this article. By Ahmed Gad, KDnuggets Contributor. co...

### Descriptive Statistics: The Mighty Dwarf of Data Science

No other mean of __data and the era of low latency decision making needs, its relevance will only continue to increase. comments By Pawel Rzeszucinski, Codewise.com Nowadays fair part of the community (often influenced by the pressure from the busine...

### Factor Analysis Introduction with the Principal Component Method and R

Share Tweet Factor analysis is a controversial technique that represents the variables of a dataset y_1, y_2, \cdots, y_p as linearly related to random, unobservable variables called factors, denoted f_1, f_2, \cdots, f_m where m \lt p. The factors a...

### Fencemarking vs. Benchmarking: How to Uncover Insights Using Both Methods

Consider a home-room school teacher who is responsible for 30 students and has access to a benchmarking service that compares each student’s semester performance to all students in the district. The teacher can review the results with students and th...

### Gulfem Karci

Burning Questions on the Future of AI When we ask the question “What’s Next in Computing?”, artificial intelligence is arguably the most exciting area of development. There has been a rapid progression in the space, and many believe we are now enteri...

### Interview Questions for Data Science – Three Case Interview Examples

Part two in this series of useful posts for aspiring data scientists focuses on case interviews and how you can best go about answering them. comments By Kaiser Fung, Founder, Principal Analytics Prep In Part 1, I described two aspects of “critical t...

### Intuitive Ensemble Learning Guide with Gradient Boosting

This tutorial discusses the importance of ensemble learning with gradient boosting as a study case. By Ahmed Gad, KDnuggets Contributor. comments Using a single machine learning model may not always fit the data. Optimizing its parameters also may no...